SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 381–390 of 3874 papers

TitleStatusHype
A Vision Transformer Approach for Efficient Near-Field Irregular SAR Super-ResolutionCode1
DREAM: Diffusion Rectification and Estimation-Adaptive ModelsCode1
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
Attention Beats Linear for Fast Implicit Neural Representation GenerationCode1
Bayesian Image Super-Resolution with Deep Modeling of Image StatisticsCode1
Attention in Attention Network for Image Super-ResolutionCode1
Deep Adaptive Inference Networks for Single Image Super-ResolutionCode1
Attentive Fine-Grained Structured Sparsity for Image RestorationCode1
Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-ResolutionCode1
Deep Burst Super-ResolutionCode1
Show:102550
← PrevPage 39 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified